IgboBERT-NER-finetuned-Final-Version

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2420
• Precision: 0.8000
• Recall: 0.8188
• F1: 0.8093
• Accuracy: 0.9751

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1164	1.0	1234	0.1290	0.6049	0.7572	0.6726	0.9612
0.0637	2.0	2468	0.1195	0.7329	0.7507	0.7417	0.9693
0.0364	3.0	3702	0.1288	0.6905	0.7683	0.7274	0.9698
0.0219	4.0	4936	0.1475	0.7554	0.7848	0.7699	0.9730
0.0172	5.0	6170	0.1592	0.7596	0.7977	0.7782	0.9743
0.0115	6.0	7404	0.1980	0.7488	0.7493	0.7491	0.9697
0.0097	7.0	8638	0.1754	0.7728	0.7758	0.7743	0.9725
0.0069	8.0	9872	0.1872	0.7473	0.7862	0.7663	0.9717
0.0058	9.0	11106	0.1870	0.7797	0.8079	0.7936	0.9744
0.0039	10.0	12340	0.2041	0.7741	0.7937	0.7837	0.9735
0.0039	11.0	13574	0.2263	0.7836	0.7964	0.7899	0.9741
0.0021	12.0	14808	0.2201	0.7867	0.7769	0.7818	0.9720
0.002	13.0	16042	0.2060	0.7842	0.7957	0.7899	0.9738
0.0015	14.0	17276	0.2047	0.7862	0.8204	0.8029	0.9750
0.001	15.0	18510	0.2270	0.7732	0.8068	0.7896	0.9743
0.0007	16.0	19744	0.2402	0.7983	0.8122	0.8052	0.9745
0.0008	17.0	20978	0.2235	0.7874	0.8244	0.8055	0.9751
0.0005	18.0	22212	0.2303	0.7956	0.8181	0.8067	0.9750
0.0001	19.0	23446	0.2424	0.8012	0.8133	0.8072	0.9751
0.0003	20.0	24680	0.2420	0.8000	0.8188	0.8093	0.9751

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1